{"id":"W4410706113","doi":"10.12927/hcq.2025.27579","title":"Developing Personas to Enable Tailored Public Health Communications: The Case of Organ Donation in Québec","year":2025,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Persona Design and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l'Agriculture, des Pêcheries et de l'Alimentation; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Organ donation; Context (archaeology); Public health; Persona; Triangulation; Medicine; Focus group; Public relations; Donation; Nursing; Business; Transplantation; Political science; Surgery; Computer science; Law; Marketing; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008485009,0.0001004276,0.0001720033,0.0002841257,0.000434698,0.00009367579,0.001092902,0.00004547009,0.000001814989],"category_scores_gemma":[0.00003530423,0.00008720339,0.00003120339,0.001797441,0.00005390502,0.0002234436,0.00008757106,0.0001737582,0.00001374814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005367045,"about_ca_system_score_gemma":0.003217093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08274748,"about_ca_topic_score_gemma":0.1857139,"domain_scores_codex":[0.998562,0.0003036982,0.0004252497,0.0002799198,0.000119179,0.0003099244],"domain_scores_gemma":[0.9981678,0.0002334149,0.0001259067,0.001141164,0.0002225811,0.0001091769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001772946,0.00005229569,0.0004273257,0.00006471865,0.000005307256,0.000004131086,0.02900042,7.907973e-7,0.00006347984,0.6475629,0.0009370258,0.3218798],"study_design_scores_gemma":[0.004972447,0.003335162,0.08044446,0.002155228,0.00002586789,0.001169319,0.274529,0.1174805,0.001435556,0.1160352,0.3957897,0.002627564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008570922,0.001298352,0.3871229,0.602118,0.00005622769,0.0006016953,0.000004703372,0.00007100641,0.000156297],"genre_scores_gemma":[0.9579135,0.00004007768,0.03432259,0.007427581,0.00001190551,0.0002287711,0.000007184931,0.000005545357,0.00004288526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9493425,"threshold_uncertainty_score":0.9233606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0781138749430381,"score_gpt":0.3485138462071677,"score_spread":0.2703999712641296,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}